Andreas
Klinger #product #metrics #marketing
Startup Lessons Learned

Follow @andreasklinger

I am a product/eng-guy good in two things:
Making people believe I am good in anything at all and making stuff worth a tweet.

On this website I share notes & thoughts.

#fyi: How founders can avoid drive-by-management

Suggestions by founders, managers, or anyone with authority in a startup, might often be misunderstood as directions or decisions. Even if we didn’t intend this to happen.

Example: A team discusses something in Slack and the founder of the company reads this for a second and replies that they like option B. Now option B is the most likely contender.

What if option A was an idea someone thought through in detail, prepared and pitched? What if the project lead knows B is a obvious but wrong idea? What if this project lead just joined the company and doesn’t know the founder well enough to say this was meant as suggestion or strong push and option A has some sort of a longer history in the company?

The founder sharing her thoughts might have caused more harm than help here. Without her even realizing. After all this was just 5 seconds for her.

Here is an article about a feature that [competitor A] just released. Didn’t we also discuss something like this? We should maybe reconsider this feature…

The founder drove by… gave management instructions (without even realizing) and is leaving the team before anyone could properly react. Drive-by management at its worst.

We all know to avoid drive-by management (getting involved without knowing enough and removing authority of project leads) but in the examples above this was completely non-intentional. The founder simply wanted to give feedback or interesting ideas they found. “Well i can’t stop talking to my team…”

The key in avoiding this, is being explicit.

I am sure - whenever you share articles in your team chat - you already add a short line how this is “just an idea” to every message. Maybe you even add full disclaimer paragraphs to those suggestions.

But even these explainers might mean very different things in different cultures.

In remote teams this problem is usally worse. A Calfornian might have “just an idea” which is actually a “very polite” (read: direct) push. But for a german person “just an idea” might be something the other person didn’t even put longer thought in. [All examples are fictious and have no historical background in the life of the germanic author living in California]

So what to do?

There is a useful method for this

The concept is developed by Dharmesh Shah of Hubspot and used by a few teams.

I got to know it via Wade of Zapier.

The core idea is the following: The team (or founder) establishes a specific code internally. Each keyword has a particular meaning, it is explained in their team-internal wiki. There it is evident to everyone what each of those statements means. And also every other manager or team member can pick this code up as well if they want.

Here is Wade in his own words about the keywords they use:

#fyi: something interesting. An article and podcast, etc. I thought you might like it. But if not no worries. Nothing to see here.

#suggestion: a passing thought. I sometimes have good ideas. You might like to hear good ideas. If I’m in your shoes, i consider it. but I’m not in your shoes so do what you’d like. A friendly response if you don’t go with the suggestion is nice, so i make better suggestions over time, but is by no means necessary.

#recommendation: I’ve thought a lot about this. Perhaps even lost sleep. I’ve invested deeply. I think this is a good plan. You can still disagree and go a different direction, but walking me through why you are doing this is kindly requested.

#plea: We don’t have a lot of mandates at Zapier, but this is one. Please do this. If you disagree enough that you can’t go along with it, we should both reconsider our roles here. It’s that important.

i use #fyi and #suggestions all the time. #recommendation much less so. and #plea is almost entirely unused.

Establishing an explicit code around this might enable you to be more precise with the reaction you hope for and it might become a habit internally that also other people can pick up.

Example #fyi: i found this article about how founders can avoid drive-by management.

As always - if i can help feel free to DM me questions me on twitter.

Refactoring larger legacy codebases

This article is based on a comment of mine to a HackerNews question. Thought it might be useful to explain it here a bit more in detail.

Questions i am trying to answer here:

  • How can you be productive in larger codebases?
  • How can you improve legacy codebases?

The #1 rule of managing legacy codebases is “code that doesn’t get touched dies” - so you want to “touch up” important code as often as possible and get into a habit of small improvements.

Here a few thoughts about how to approach this…

1) Get the team on board

If multiple people are working on this codebase, you need their buy-in and support for whatever approaches you together choose to implement.

2) Plan for “health by a thousand small improvements.”

Legacy code was created by “death by thousand cuts”.

You won’t be to fix everything in one big step. You won’t be able to stop working and “refactor everything”. And more importantly, you shouldn’t do it. It never works out.

This refactoring will be an iterative approach over a longer time. Your goal is to refactor parts as you go.

3) Don’t assume different = bad

People who worked on this codebase might have done differently in the past. Those might be different than how you would do it. Invest in understanding their approaches and consider using them. Consistency beats beauty in codebases. Codebases get bad if multiple people try doing various different approaches. Don’t be one of them, whenever you can.

4) Create space

Consider introducing a Fix-it Friday.

The rule of Fix-it Friday is simple: unless your current project is on fire, use Fridays to invest in little improvements. Let engineers choose on their own what they work on. Try not to take the “fun” out of this by micromanaging. Some will try out new libraries. Some will remove bugs from the backlog. Both are fine. Try encouraging a balance of tasks.

Encourage these improvements by summarizing them (eg weekly in Slack) and maybe use them for quarterly peer reviews.

5) Create non-blame culture

Stuff will break if people risk improving things. Avoid shifting blame to them.

Those things can be subtle. Example: bug trackers might ping people individually, consider pinging the whole team instead.

6) Automate whatever you can automate

Introduce linters, auto-formating, code-mods, ci/cd tools, danger.js, code complexity analysis, etc. Use tools like (eg) lint-staged to encourage step by step improvements on new code.

7) Introduce tests

This one is the most annoying parts, but worth doing: whenever you improve a feature try adding a test. Do this step by step. Consider the tests a form of documentation explaining what the functionality should do.

A lot of people recommend writing a test suite for the whole app before you do anything. If you are lucky enough to do… well… this try it. I always found the iterative approach more realistic as you can also do feature work while refactoring. I also was usually never able to add tests unless i worked actively on a feature. But you are not me, try it maybe it works for you.

When doing tests focus on integration (vertical/functional/etc) and not unit tests (unless the “unit” contains critical or complex logic).

Your goal is to know “that you broke something”, it’s ok not to know exactly “what you broke”.

8) Acknowledge tech debt

Not everything needs refactoring.

If it’s not critical, or nobody needs to improve its functionality in the next months, or it’s just too complicated, consider acknowledging it as tech debt.

Add larger notes above the problematic areas and explain why you aren’t refactoring it, explain things that might help the next person understanding the code better, etc.

Whenever you leave comments, remember that comments should explain “why” not “what” the code does.

You should notice improvements quite quickly (a few months in).

Good luck!

If i can help somehow feel free to send me a DM via twitter!

A model that’s mental

Maybe…

This anxiety isn’t anxiety it’s just your raw excitement that you are misunderstanding.

This creeping imposter syndrome just means you are challenging yourself.

This slight panic before you show your work means you care a lot about quality.

This dreadful feeling during meetings to come up with something smart to say means you are with the best possible people for you.

This anger when things don’t work out or people live up to expectations is just hope and passion being a bit too loud.

This feeling of wanting to scream and run through any wall means… well… i don’t know… maybe get that checked out. ;)

This feeling of being sometimes overwhelmed means you push yourself to move fast.

Maybe you are not too weak or too crazy.

Maybe this is normal. Maybe you are normal.

Maybe everybody has those feelings. Sometimes more, sometimes less.

Maybe you challenge yourself, and that’s good. If you wouldn’t challenge yourself, if you wouldn’t care, you wouldn’t have those feelings.

Maybe try to see your fear, acknowledge it, appreciate it, thank it, and know it’s just your attention being awake.

Maybe try to see your worries, acknowledge them, appreciate them, thank them and know it’s just your love for detail.

Maybe knowing this, you keep going on and you realize you can manage this and all tasks in front of you. And once you get good at them maybe go and challenge yourself with something else.

But maybe… no not maybe… definitely… yes definitely… make sure to look back from time to time and see what you already achieved. All the steps you did, all the fears you faced, all the anxiety you felt and embraced and then learned to love; all of it became the excitement you needed.

Then when you are done with looking back, look forward again, smile and keep trying harder. Keep challenging yourself.

Written for us both to remember.

Why i wrote this post:

This is not meant as medical advice whatsoever - and anxiety is different for many people. I am also not saying “push through no matter what”. I am just trying to share what helped me.

I struggled with anxiety after my first startup crash landed. I had a burnout. It led to me overthinking and being afraid of every decision. I remember vividly being invited to a friend’s dinner where everyone was supposed to bring a salad. I freaked out because i didn’t know what salad to bring. Fruit salads are easy and people like them. Right? RIGHT?? But I couldn’t decide which fruits to use so i bought them all. The bowl ended up being huge. It was so much that we used the leftovers for several bottles of smoothies.

A bit later things got better, but i noticed that i still had anxiety in situations that should have been… well… exciting.

It got a bit into my way. I messed up situations, that i shouldn’t have messed up and blocked potential paths for me that i would have loved to take. I got angry about this, which helped neither, as you can guess.

I tried multiple things. Pushing it down, breathing, meditating, binge-watching, whatever. Nothing helped. If I situation was too much: Light anxiety! Once i realized it: Hello big anxiety!

At some point I tried a different approach: I started to tell myself that anxiety is just misled excitement.

I don’t know why but it felt right.

And more importantly, it let to a rethinking of my situation. Instead of being angry at myself for being anxious i started to be thankful for my body trying to help me. I began to appreciate this feeling, maybe giggled about the weirdness, loved it for making me happy with giggles and moved on with this little unexpected newly found excitement bump.

Nowadays when stressful situations arise, i notice how i have honest excitement. Maybe it’s due to this method, perhaps i just got over the burnout, but no matter which of the two it is, I hope reading this article helps you too.

Because…

Maybe…

This anxiety isn’t anxiety it’s just your raw excitement that you are simply misunderstanding.

Managing Remote Teams - A Crash Course

Hey folks,

I haven’t been blogging for quite some time, so everything is a bit rusty for me, but i thought this article might be useful for a few more people, because about 1-4 times per week i get approached with a question like:

  • “Should we do remote?”
  • “How did you remote work for your team?”
  • “Our team struggles with engineers who are remote…”

The post got a bit longer than i planned to, because i tried to cover the outline of all aspects that might be useful for you when you approach this topic. In this article, i will go over the different kind of setups of remote teams, why and how remote teams work differently, when you want to work remotely and when it’s better not to and lastly a few tricks that worked for the teams i was involved. Thanks for reading and thanks for sharing. 🙏

For those who don’t know me and just stumbled into this post by accident: I am @andreasklinger -among other things - I helped to build up Product Hunt as a fully distributed team. Btw… yes, they are awesome, yes, they hire internationally, and yes, you should consider applying.

So here without further ado… here… we… go.

Remote teams - a crash course

Different setups of remote teams

There is a bunch of different setups people call “remote teams”.

  • Satellite teams
    • 2 or more teams are in different offices.
  • Remote employees
    • most of the team is in an office, but a few single employees are remote
  • Fully distributed teams
    • everybody is remote
  • Remote first teams
    • which are “basically” fully distributed
    • but have a non-critical-mass office
    • they focus on remote-friendly communication

When i speak of remote teams, i mean fully distributed teams and, if done right, remote-first teams. I consider all the other one’s hybrid setups.

Why does the distinction matter?

They are actually something entirely different and need different solutions.

Process needs

As a remote team, you have roughly 5x the process needs as you would in a co-located team.

Example: Meetings

Everybody loves meetings… right? But especially for remote teams, they are expensive, take effort and are – frankly – exhausting.

If you are 5 people, remote team:

  • You need to announce meetings upfront
  • You need to take notes b/c not everyone needs to join
  • Be on time
  • Have a meeting agenda
  • Make sure it’s not overtime
  • Communicate further related information in slack
  • etc

In contrast, if you are 5 people co-located you just stand up and say: “everyone over there - we talk now”. Once a co-located team reaches 20-25 people they definitely need to do the same steps. But before…

You can’t just “get up and talk with everyone all the time” in a remote team… you simply can’t. People might be offline, might be sleeping, might be deep focused on other work.

And this is not only about meetings. Meetings are just a straightforward example here. It’s true for any aspect of communication or teamwork. Remote teams need 5x the process.

You need to systemize communication and expectations

When i say processes, i don’t necessarily mean heavy-handed workflows, piles of paper and someone using a giant stamp confirming every action. I mean “systemized communication and expectations made explicit”.

This can be as simple as: “We do check-ins every morning…” “Please before you do X always do Y…” These simple explicit agreements allow other people to expect those actions to happen and avoid unnecessary communication loops.

But… i am sorry to say… this is work… you need to act like a larger company than you actually are… you need to be stricter about best practices, and you will run into communication problems… a lot of them.

These communication problems are often what people complain about when they discuss if they should switch to remote teams or hire remote engineers. So they consider hybrid setups…

Hybrid setups are hard to do

Imagine you are the only person remote in a small team. You have entirely different process needs. You will suffer.

Being the one poor soul remote in a co-located team is hard… you have “5x” the process needs… People will continuously forget to involve you in discussions or decisions, you will be the person not knowing what is happening why - you will suffer.

Similarly problematic are satellite offices. The bridge between the offices has 5x communication needs, but people in each office act like co-located teams. Unless the offices can work mostly autonomously, this communication bridge between them will suffer.

Establish processes for communication needs for these kinds of setups are hard. Because they are against human nature… I will just discuss things with you while getting water in the kitchen… I won’t repeat what we discussed in slack because i am… well… as all humans… damn lazy!.

Default remote or default non-remote?

I have tried all the models described. Personally, I’d recommend you avoid hybrid approaches and act as distributed as possible - or just don’t do remote at all and be co-located. Both are fine.

If you need a small office, make sure people in it don’t have a critical mass in projects and communicate remote-friendly.

In these situations, the question is often “Are we default-remote” or “default non-remote” if it’s the first, having a small office might work out for you.

Questions to ask yourself:

  • Why do you consider doing a remote team?
  • Are those advantages worth the effort for you?
  • If yes what would need to change if you would commit to it?
  • How often do you want to meet in person?
  • If you need a small office how can you communicate more remote friendly?
    • Example: Would it be weird if all people in the office would join team calls with their own laptop?

Why would a team want to work remotely?

A lot of people mention costs. “It’s cheaper to hire people remotely”. This might be sometimes true – and it’s definitely true if you are used to San Francisco salaries – but… international talent usually expects international salaries… so you’d be surprised how much many people expect. If you want cheap outsourcing, this “remote thing” won’t work for you.

Overall hiring remote is about four things - being able to hire, the best possible people independent of where they (or you) are - optimizing for the quality of life - tuning your personal performance - having long-term team retention

“Our startup is amazing, people will want to move to X"… Some will… some won’t. All the "won’t” are a lot of people you are missing out.

On the other hand with a good remote-team pitch, you can even (often, not always) approach Silicon Valley top talent: “Hey considering leaving the Bay Area? Google might have an issue with it, we don’t - work with global talent on a project that matters – wherever you are. Shall we talk?”

But (imho) what most people are missing… is not the costs… not the untapped talent… nor the ability to optimize your quality of life and own performance. It’s a simple fact: talent retention. Ask remote teams how long their people stayed with them. It’s years longer than in co-located companies.

Iteration vs. innovation

One thing you will quickly realize is that a lot of human nuance gets lost when discussing things via Hangout or Slack. This nuance is important. Especially if you work on critical, creative work.

Imagine you need to pivot your product. You make a long passionate speech about what the team needs to do to win the market, just to be followed up with a “Sorry Sarah, your internet connection dropped for a second, what did you say?”

“Innovation” is more natural in person. It’s better when even the quiet person in the back can pick up a marker and explain something.

But once you agree on something it’s about individual performance… This is usually easier remote.

  • Iteration easier remote
  • Innovation easier in person

So even if you work remotely, you will need to define how often you want to meet. I recommend once per quarter or twice per year as a team and whenever required by the individual project teams.

Loneliness

A lot of people mention loneliness as a problem in remote teams. Personally, i never had this an issue be for me, but i saw it with friends and fully understand why people are worried about this.

As company-lead it will be your responsibility to make sure people are happy and healthy. Here is what helped in our team:

  • Don’t work from home but a shared office (coworking spaces tend to be too distracting)
  • Make sure you meet non-work friends
  • Meet regularly in person

Optimize for iteration - Optimize for single player

In remote teams, you need to set up in a way people can be as autonomously as they need. Autonomously doesn’t mean “left alone” it means “be able to run alone” (when needed).

Think of people as “fast decision maker units” and team communication as “slow input/output”. Both are needed to function efficiently, but you want to avoid the slow part when it’s not essential.

Questions to ask yourself:

How can you…

  • … define strategy clear enough that people can formulate their own decisions without going off-track?
  • … set goals clear enough that people can benchmark themselves or their decisions?
  • … setup decisions hierarchies in a way that only non-reverse-able important decisions even bubble up to you?
  • … create confidence? (speed comes through confidence)
  • When is it enough that you hear about it and when do you need to involve?
  • How can you make sure that you are only involved in every 10th decision and only “manager-override” every 100th?
  • … set up your environment/processes that they can act even in emergencies on their own?

If you hired smart, talented people, why can’t you just “let them do their job”? What’s missing? Did you hire the wrong people? Did you not communicate clearly? Are you (yourself) uncertain about strategic elements? Solve that instead of micromanaging them.

Apart from these company-wide questions, you will want to ask similar questions also for each specific vertical.

Digging deeper: managing remote engineering teams

Here a few example questions for engineering teams (but you will know similar ones for any kind of function):

How can you or someone in your team…

  • … troubleshoot alone when it’s in the middle of the night for everyone else?
  • … enable new developers to be able to learn by themselves?
  • … guide coding best practices?
  • … avoid making pull requests a slow process?
  • … prevent meetings that don’t create value?
  • … enable developers to make product decisions on their own?
  • … avoid worst case scenarios?
  • And again: How can you increase confidence? (speed comes through confidence!)

At Product Hunt we thought a lot about this! Here a few answers that helped us:

  • Have a clear strategy and high-level goals
  • Let engineers take ownership over teams and projects
  • Let them take ownership over the product they build, but also the goals they commit to (strategy goes top-down, execution bubbles bottom-up)
  • Making it clear what scenarios require multiple eyes or other people’s feedback (e.g., stack changes, security concerns, etc.)
  • Have strong onboarding documents and employee handbooks
  • Have new employees improve those onboarding documents
  • Be explicit in communication
  • Be explicit which are expected rules and which are not.
  • Wait for problems before you introduce solutions (esp. processes or infrastructure)
  • Friday’s employees can work on what they think creates value (unless their project is on 🔥) - fixing tech debt, improving UX, trying out new libraries, refactoring infrastructure,…
  • Share recorded videos instead of live-demos to explain something (e.g., UX prototypes)
  • Have a strong (but not too big) test suite (focusing on integration for features, unit tests for risky parts)
  • Focus on reuse of standard components instead of pixel-perfect layouts
  • Enforce linters for any language you use (even, e.g., HTML/CSS)
  • Enable autoformatting (to avoid code style discussions)
  • Enforce complexity scoring in linters (⬅️ biggest win)
  • No production console access unless for (logged+alerted) emergencies
  • Make it easy to recreate a production-like state in development (sanitized)
  • Have one-step-to-reinstall development environments
  • Have defined times for pull request reviews (first thing every morning)
  • Make Pull-request +1’s a “polite thing to do” but not a “required step”
  • Enforce pull request +1’s for parts that are security risks (via danger.js)
  • Write comments about why not what
  • etc. etc.…

Let me know if you think it would be useful for you if i’d wrote a larger blog-post going into detail here. For now, there is a lot more detail about we worked at Product Hunt in this first presentation of mine: https://www.slideshare.net/andreasklinger/engineering-management-for-early-stage-startups-97402850

TL;DR: The ultimate goal of this setup is that an engineer can figure out, on their own, if they are doing things right or wrong. Have low-level feedback coming from automation and that it’s clear when high-level feedback is needed from team members. And most importantly you treat them like capable adults.

But… these are not problems of remote teams

The problems i mentioned are not unique to remote teams, and the solutions are the same thing good co-located teams do. But they don’t need to be as strict about them because they face them later of can just monkey-patch around them. Their engineers might not like the typical “let’s all get over there and talk…” But i tends to work… so people do it anyway.

co-located teams monkey-patch their process problems with more meetings and micro-managing people.

As a remote team - because of the higher process needs - you just end up facing these knowledge worker management problems earlier and more intentionally.

Because meetings are expensive for you, you need to think about systemizing processes actively.

Because you cannot watch over your employees’ shoulders, you have to find ways and boundaries you can fully trust them.

Because you cannot micromanage them, you need to define strategy and goals and treat them as competent adults who make decisions for you.

Aren’t you already working in some way?

We can discuss the pros and cons of remote work, but let’s be honest…

We are all already working remote… You might be checking your emails on your weekend, you might be reading papers on your way to work, you might finish some project in the evening at home. You already work remote, the question is only how often and how much enabled you are to do so.

The question is no longer if you work remote but how much.

Remote work is the logical evolution of digital work. And the best-practices of remote teams are often learnings for all digital knowledge work teams.

The end

Let me know if this is useful… And if you have experience with remote teams, tell me how i could improve this article! Also last but not least: Please share this article if you think it’s of value!

PS: I haven’t been blogging for years… I was very nervous about starting to write again and asked for early feedback. Over 100 people offered their help, more than i can mention here, i am still at awe about the fantastic feedback i got. The offer to help means a lot to me. Thanks to everyone.

If you want to help me by feedbacking early drafts of my blog-posts please subscribe here. Thanks in advance

🙏 @andreasklinger

The simplest and most important dashboard for early stage startups.

This blogpost is part of a small series of posts that cover the basics of startup metrics. My personal goal is to help early stage startups more effectively, but also avoid repeating myself too much in mentoring programs.

If you are working on a software product in early stage of its lifecycle this series might be useful for you.

Other posts in this series.

If there are special topics you’d like me to cover please ping me via @andreasklinger. Also if you consider them useful please be so kind and tweet this article.

Early Stage Startup Metrics

One of the most common pieces of advice is that in early stage you want to focus on retention. Because retention - in the end - is a function of customer happiness

retention = f(customer happiness)

It’s simple: If people are not happy with your product and/or gain no benefit by using it they will most not continue using it.

And automatically cool visualisations like retention cohort tables come to mind.

While those tables look nice and give you this nice fuzzy feeling of doing something useful with your time, they are unfortunately usually a bit useless until you get to the point of optimising on-boarding conversions of new users.

Please don’t get fancy too early.

This kind of visualisations are great when you have too many users and need to get a bird eye view. When you need to an abstraction. B2C mobile apps often have this problem already in early stage. But most SaaS companies (or companies still in beta) i worked with don’t have this problem until they reach product market fit.

20% changes with 20 customers won’t tell you much apart of the basics of standard deviation. A personal relationship to this customer will tell you his story. Keep them close.

If you treat your paying customers like percentages and meaningless numbers they will do the same with you.

The one “dashboard” i recommend almost all early stage startups is one they already have. Let’s start using it.

As long as your customer list fits on one or two pages, you should have a list of all those customers. (And i am pretty sure you already do have this in your backend)

Add activity information to this table. Core KPIs that tell their activity level (or at least their last login date). Color highlight it based on activity. And put someone in the team in charge of making sure everyone stays on green.

dummy mockup is dummy

Seriously? That has nothing to do with metrics, or?

“That’s the kind of advice gives someone who charges money for consulting? Make him draw complex graphs or bring the pitchforks.”

This dashboard so embarrassingly simple to implement, i was even scared to publish this post. But it is - and keeps being - my most common recommendation for a custom dashboard.

I don’t know about you. But I don’t necessarily need numbers. I need information i can act on. I want product insights - simple ways to use my database information to create actionable insights.

Most abstractions like graphs, retention cohorts, aarrr funnels and so on are great to aggregate information as soon as you have too much of it. Before that they just do one thing, create an abstraction layer.

For myself i found out this is even useful in a bit later stage: If you have only 0 - 100 new signups don’t hide them neither. It’s the same game on a higher level. Their first month is the one month that decides if you will keep them or not. Keep someone in charge of making them stay green.

Put one person in charge of keeping all customers on green. Most likely that person is you.

Your job as a product manager/founder is it to keep in contact with all those customers. And as soon as someone moves to orange contact them via email or skype.

Find out what’s going on. Now they are still in their decision process. Now you still can convince them to stay. Now you might even get useful information for product changes.

Churn is not happening when a user unsubscribes from your service or stops paying you. This is just when you notice it. Churn happens when a user stops using your product. You want to jump in when a customer is at risk, when he might stop using your product.

As long as you have a few dozen paying customers you can contact each one personally. There is no excuse. Don’t treat them as numbers, if you don’t want to be treated the same way.

Customer Happiness Index

If last activity of your customer doesnot mean much for your product (eg login might not mean that he found/did something) you might want to focus on deeper core activities.

Usually people create a Customer Happiness Index. A single number that combines all done activities to a sum, while giving each of those activities a weight.

By doing that you can eg. say that logins are less important to you than purchases. You can even aggregate those numbers in groups and through that see problems in certain segments of your user-base.

But to be honest, as fancy this is, i hardly ever need this.

Not until i need to aggregate those numbers. Eg show the customer happiness of a certain customer segment.

But until then - in my personal experience - i usually only see 1-3 core activities in a product. (eg in a project tool - number of projects/total, todos-closed/week, active-team-members/week) And normally i tend to simply recommend adding those numbers to the table and be done with it.

Commercial break.

One product i want to highlight at this point is Intercom. They basically offer this as a service, but add manual and automatic messaging. Additionally they write one of the best startup product blogs out there

But as long as you need/want to save a bit of money. The table mentioned above is only a few lines of code away.

until then, get your product moving,

Andreas

Easy, but easy to f*ck up. 3 Rules to Setup Analytics Tools correctly.

As a consultant for analytics i see a fair share of integrations of analytics tools. One of the most common mistakes is how people actually track events and conversion goals.

Very often a lot of data is rendered useless because it is confusing or contradicting to each other. If people use several tools. This problem even amplifies more.

I summarised my personal opinion in this tweet above. People asked me a few times to go into details - so here are some quick notes.

Btw if you look for a bird-eye view on the whole topic of metrics tools check out my ebook-as-a-mega-blog-post: A Primer on Startup Metrics.

Rule #1: As few actions as possible

You want to add as few events as possible.

“But we need to track so many things”

If you starting out, do yourself the favor and ignore everything that “might be interesting” (optimisation) and focus on the ones that define the core aspects of your product (accounting).

Things will break, the less moving parts you have the more certain you can be that they actually still work and provide meaning.

Protip: use a prefix for temporary events. I use “test_”

Rule #2: Triggered by the same logic in code

The most common mistake is to have analytics events triggered in different parts of the application.

Eg. Google Analytics might receive the event when the user presses the button or visits some page “that should come afterwards” and your custom dashboard pulls the data from the database.

This sound reasonable in the beginning but very soon your application will change a few times, new validations will require more complex forms, etc, etc. Very quickly you have a mess of interdependent logic that will lead to stuff breaking.

My recommendation: Create a analytics helper function that you trigger at the place the actual event happens. Eg in case of a user signup AFTER the user is saved. If you send your data to your analytics tool through javascript it’s the job of this helper to make sure the frontend receives the needed information. (eg in rails use gon or flashes - watch out for 301s)

Rule of thumb: If data change happens the event should be triggered at the place the data change happened.

Rule #3: Same names in every tool

One of the biggest mistakes people do is to use different names for kinda-the-same things when they use different tools.

Use the same name, make it the job of the helper to make sure every tool receives the information in the format they need.

Eg Google Analytics might expect “User”, “Signed Up” and Mixpanel might expect “User - Signed Up”

Btw Segment.io is a wrapper for your analytics calls and highly recommendable (they additionally offer features like history import to new tools, etc).

Rule #3.1 Event Names: Be understandable

I - as somebody who has not implemented your events - should be able to understand what each event represents AND in which context of your app it is most likely triggered.

Rule #3.2 Event Names: Be explicit

If a user has been created - this happened If a user just clicked a button - this happened

Eg Newsletter Submitted is not the same as Clicked Newsletter Submit Button

Nothing is more horrible than ambiguous event names.

Btw In almost all cases you will want to use past tense.

That’s it

I hope this primer helps you to set up your events correctly - if you have any questions please feel free to reach out to me via twitter If this post is useful for you please tweet and share it. Thanks

Until then, track on

Andreas

A Primer on Startup Metrics – Which Analytics Tool to pick.

As a analytics consultant I am working with a lot of startups and help them in the topics of metrics, analytics, retention and growth. Most of the questions i get are based on a few misunderstandings.

Eg. What kind of analytics tools you should use depends what you are trying to do with those tools. They have (more or less) specific purposes.

Disclaimer: This post focuses on web products - but you could apply the same concepts for mobile.

The Segmentation of web analytics

So let’s get into this…

First: Please lower your expectations

If you are hoping to add one tool and be ready to go, i need to stop you right here. Please readjust your expectations.

There are a few hard truth facts we need to accept:

All tools are good for a few things, but tend to suck for most of the other - the trick is to know what you are looking for.

Also: Any tool you will integrate will most likely be: not optimal for all of your usecases, not specific enough, most likely be broken or incorrect a good amount of your time and contradicting every other tool you have.

But that’s ok. If you know how and what to use them for.

Let’s roll…

I personally split usage of analytics into two axis:

  1. exploration / accounting.
  2. external / internal

Exploration vs Accounting

Exploration are those ad-hoc questions.

Exploration are all those quick questions people come up with and are very often related to some intuition we have.

  • eg “What feature is most used?”
  • or “Are users who use feature X more likely to upgrade to plan Y?”

Conversion Rates, Landing Page Optimizations, Funnel Optimizations, Viral Loops, Quick questions and insights are they typical examples of usecases of exploration.

Accounting are the metrics we track over time.

FYI the term accounting was coined by Eric Ries as innovation accounting covering more metrics than the typical product metrics, but the term kept sticky in normal web analytics as well.

If you have ever kept record of KPIs in your excel sheets (eg for investors) that’s a typical report we want for accounting.

But it also includes reports here we tend to use several times a week.

Cohort Retention Tables, Customer Happiness Reports, Traffic Referral Reports or Revenue Reports are typical examples for accounting reports.

About Data integrity

In case of exploration it usually doesn’t matter too much if we have only little historic data, or that we need to jump through a few hoops (aggregate from several tools, export to excel/R, etc). We need as much data as we need to invalidate or validate our hunch/gut-feeling or current objective. Very often this insights can and will be challenged by the team and need further verifications.

These insights usually lead to experiments (eg a/b tests).

In the case of accounting it is very important to have historic data and data integrity is very important - we can’t really tolerate too much noise in the data we are using for accounting. We can’t really tolerate broken reports nor can we have our team not trusting those reports.

This insights usually lead to strategic decisions. (eg switch sales focus)

While it is very useful to distinct between these two areas we need to keep in mind that in reality the lines are a bit blurry.

The second axis i tend to look at is external and internal analytics.

External vs Internal Analytics

  • External Analytics covers all public facing pages and all passive actions by users (eg views).
  • Internal are all actions done by (persistently hopefully) identifiable users, that potentially reflect if your product provides value to them.

When people speak of “product insights” they tend to mean that internal view of your product.

Many product have a very clear distinction between external and internal - eg. SaaS tools provide a value that i need to register for.

Sometimes it’s a bit blurry - Some products provide usecases to non-identified users as well - eg. content pages like pinterest or 9gag where a huge amount of the product is public and most of the visitors value is provided passive.

In a nutshell

Which Tools

There is roughly a million of analytics tools out there. I will focus in this article on the most common ones for web products: Google Analytics, KISSMetrics and Mixpanel.

Google Analytics:

GA is great for everything external. Especially traffic analysis and referral optimization work perfect in GA.

I am a huge Google Analytics geek and to cover it properly would be at least 3 own blog posts.

If you are new into it here are three blogposts i would recommend you to read:

The most common usecase for GA is referral optimization. It enables you to understand what sources bring you the most valuable traffic and where you should double down (as said above learn how to use weighted sorting).

If you use GA for all external stuff you will be very happy. For product internal insights GA tends to be useless.

The main reason is that GA doesn’t think in users and events. It thinks in visits and sessions.

You can force GA and focus more on visitors, you can segment down to the pages that are product internal, people that are registered and you could look mainly at events. But even if you do all of that then you will have a hard time using that data.

GA wasn’t made for product insights in first place.

GA is awesome for product-external exploration and very good for a lot of product-external reporting/accounting (eg weekly referral/traffic/seo reports).

But it stops being spot-on useful where most products actually start. (activation/engagement)

Ad Mobile: I am speaking obviously mainly about GA for web here. The GA team currently pushes their mobile analytics tool. Everyone who has used will notice this weird feeling that the tool wasn’t meant for this originally in first place. But given their current development speed I wonder if i will need to come back here in half a year to update this part.

KISSMetrics and Mixpanel

Both - KMS and MXP - come from the same main concept. They think in “people” and “events”.

Both tools are great and to cover them well would need several blogposts by themselves so please excuse my brevity.

At first they look very similar and i am pretty sure you could substitute every feature of the one in the other. But to me they both tend to have a bit different focus. They have been build by teams with a bit different values.

Mixpanel is awesome for product-internal exploration and good for product-internal reporting. It’s the tool i would pick if i focus more on product improvements (eg engagement). Personally I also have better experience with its stability.

KISSMetrics on the other hand feels like it has one foot in the product-external world.

It’s revenue tab makes it very easy to see what sources brought customers of what kind of life time value. You can easily see what your customers where doing and so on.

Of course MXP is catching up and offers a revenue tab as well. But nether the less KISSMetrics would be the tool i’d pick if I would focus a lot on revenue improvements (eg through content marketing) while trying to improve the product itself (especially as a SaaS startup)

Actually KISSMetrics fits so well as a hybrid between product-internal and external usecases - especially for content marketing - i wouldn’t be amazed if they come up with a specialised content marketing tool or somehow else integrate with Google Analytics to have a easier angle to the market.

Specialised tools

There are a lot of really good specialised tools and again not possible to cover all of them here. My personal four favorites are

And of course there are many more.

The advantage of specialised tools is that they understand (or expect) enough of your product internals that they can provide value insights right out of the box.

The big problem with all tools

Most tools are integrated through push events. Basically your site will send an event through javascript or your backend and let their service know.

There is a big problem with this approach.

Data Integrity

Sooner or later your integration will break for a day or two. Because someone on their or (more likely) your site made a mistake.

Sooner or later you will change how you track certain events and your comparison with your historic data will no longer work.

Did you ever see different numbers in different tools? Eg different amount of registrations between MXP and your database? or Revenue in KMS and in your stripe dashboard? Well that’s what i am speaking about.

In case of exploration this usually tends not to be a big problem. Anyway the data i work with tends not to be optimal (sample noise, dataschmutz, skewed, variance etc) and I am just looking for anchor points for future experiments.

In case of accounting this is a big problem. We cannot really have our revenue reports incorrect. This is unfortunately where the fun ends.

And there is a other problem…

Focus on product internal aspects

Very often product-internal reports tend to be quite specifically tied to your product.

  • If you run a market place you want to report improvements on both sides separated.
  • If you sell not to people but to companies you want to aggregate your users into those company buckets.
  • If you have different levels of users you might want to treat them different (eg drill down your best paying or engaged segment)

To figure the right metrics is a blogpost by itself but to in a nutshell you want to tie your product assumptions to quantified results.

All of the mentioned segmentations above are doable in some tools mentioned, but it will require you to jump through several loops.

And given the fact that very often data integrity tends to be a problem the logical conclusion is to sooner or (if possible) later build those highly specific reports by yourself.

Work with your database for accounting

When it comes to accounting i would highly recommend to work with your database.

As a rule of thumb: The more you need to zoom in - the better you work based on your own database.

Depending on the level of complexity you need you can:

  • Export to excel
  • Run a script that sends the most important numbers
  • Build a simple dashboard

In most cases i would recommend to start with the first one and do it for the first months. And then start step by step automating the most time consuming report parts to scripts and from scripts you will move to a simple dashboard view over time. Usually i would recommend stopping here.

If the dashboard itself turns out to be too time consuming (eg most likely because you put too many expectations into it) try using a tool like chart.io

If you pre-run into performance problems move the analytics to a own server and run the scripts only once a day.

Doing that you can introduce reports like Customer Happiness Index and Health Dashboards (red/green lights (or kpis) per customer or segment)

Disclaimer I am not advising you to build your own analytics tool. I not recommending to measure non-logged-in data. I advice you to segment your existing database data for reporting. There is a big (costly) difference.

I won’t go into dashboard design right now - but if you are interested in this topic please let me know via twitter happy to write a blogpost about it.

So to answer the question – which tool would i recommend

These are the swiss army knifes. Depending on stages i would recommend other tools additionally or instead.

If i have to decide between MXP and KISSMetrics i would - usually - go with Mixpanel (but as explained above it depends a bit on the specific product).

Hope this blogposts helps you a bit to get clarity about metrics even though i couldn’t cover all aspects nor all tools.

If you are still unsure which tools to pick i would recommend using Segment.io as a wrapper for your API calls. That way you can simply replace your tools whenever needed.

If i can help you anyhow with your analytics setup - let me know - i am doing weekly open office skype sessions - feel free to hit me up on twitter

Until then - measure/build/rock

Andreas

Don’t drown in email! How to use Gmail more efficiently.

I usually I blog about Angellist, Startups, Founders, the Future and especially Metrics but I have shown this “lifehack” to so many people that I thought it’s worth it’s own blogpost. Hope it’s useful.

If you struggle with keeping on top of your emails in Gmail you want to maybe try my setup. It’s hard for me to lose track and trust me - i am easy to distract

This is how i use Gmail since 2010:

  • GTD - Getting things done
  • An easy to manage, usually empty inbox on the left
  • All “todos” in the first box
  • All emails “awaiting a reply” in the second
  • All “delegated” emails in the third
  • All emails related to meetings, flights, etc easy to find in the fourth
  • All done with 0 plugins, using only standard gmail features

It’s hard to lose overview using that setup

I couldn’t even imagine using gmail any other way. No seriously. I see those messy priority inbox tab inbox systems and I am just scared. Scared that google will someday force me to use those features.

Btw: This approach is not particularly new. I learned it from a person (forgot name) at LeWeb 2010 and it was mentioned on a blogpost which was called “Gmail Ninja” (couldn’t find the link).

How I manage daily work

  • An email comes in
  • Handle those you can instantly
  • The others mark as todo
  • If you want to keep track of them when you replied, you mark them as “Awaiting Reply” or “Delegated” (that way you can always quickly find them and follow up)
  • You archive all emails
  • You inbox on the left is empty again
  • All important ones are in the special boxes ones the right

Example:

  • Received an email
  • Was able to reply instantly (if i wouldn’t have had the time i would marked it as yellow bang (Todo))
  • I replied
  • Marked with “awaiting reply” (question mark)
  • Archived the email
  • The email is no longer in my inbox but in my “awaiting reply list” on the right side
  • His reply will come into my inbox (and we start over with replying instantly or marking as action)
  • Archive - Inbox Zero

That’s it! You are done.

Hope fully that workflow also helps you.

Interested? - It takes about 15minutes to set up…

… but might change how you work with email forever ;)

In a nutshell it’s

  • Multiple inboxes
  • Special stars
  • The multiple inboxes have searches matching the special stars
  • Several filters to avoid repetitive tasks

Step by Step guide

Add multiple inboxes

  • Go to Settings (you will find it under the cogs icon on the top right)
  • Go to Labs
  • Enable Multiple Inboxes
  • Choose right side layout

Choose the correct special stars

  • Go to Settings > General
  • Scroll down to Stars
  • Add the stars you will want to use

I use:

  • Yellow bang for Todo
  • Red bang for Important Todo
  • Question mark for emails I expect or await a reply. (so i can followup)
  • Orange guillemet (double arrow) for emails i delegated to someone but expect to be done. (so i can follow up)
  • Purple star for any arranged meeting, flights, event tickets, call or anything else related to an event where i might need to find that stuff quickly.

Filter the inboxes to match the stars

  • Go to Settings > Multiple Inboxes
  • Switch to right side layout - the option is in the bottom (!)
  • Add the filter rules you want for your inboxes

Here is the list of all names of the stars:

  • has:red-star
  • has:orange-star
  • has:green-star
  • has:blue-star
  • has:purple-star
  • has:red-bang
  • has:orange-guillemet
  • has:yellow-bang
  • has:green-check
  • has:blue-info
  • has:purple-question

You can btw also do more complex filters by adding OR, AND or basically anything else you can use in search. Eg. I use OR to show both important and VERY important todos.

Note on mobile: If you use the mobile Gmail App a lot i would suggest to use the normal yellow star for todo. That way you can at least mark todos in mobile. Unfortunately the other features won’t work as well because the gmail app doesn’t support them.

Enable the inbox layout (aka kill the tabs ;) )

This part is a bit annoying - basically you need to disable a lot of fancy default features of gmail. If the new multiple inbox layout doesn’t appear in your inbox after you finished the guide you might have missed some step here.

  • Go to Settings > Inbox
  • Switch to “default”
  • Turn off any configuration you might have regarding tabs
  • Turn off any configuration regarding priority, important emails or filters

  • Go to your inbox
  • Click on the cog and click on “Configure Inbox”
  • Remove everything
  • And while you are at it: Switch layout to “compact”

Now reload

Getting to inbox zero the first time

Let me guess you got a lot of emails in front of you right now or? I had several thousands the first time.

You need to get from several thousands it to Inbox Zero. And this needs to happen now. But it’s actually quite easy.

  • Go through the first two or three pages of email.
  • Mark everything that is a todo with a todo icon (in my case yellow bang).
  • Every thread where you had the last email and await a reply mark with your awaiting reply icon (in my case question mark).
  • The same for your delegated and events emails.

When you went through the first two or three pages and you have the feeling nothing (still) important appears anymore do the daring move.

  • Click select all (the checkbox on the top left)
  • Confirm that you really mean all 6523 emails
  • And click on archive

Now your inbox should at zero and your right areas full.

More Gmail Workflow Tips

If you like the suggestion above you might be also interested in my other gmail workflow tips:

Robot the majority of your emails

I am pretty sure you receive dozens of newsletters, groups etc.

  • Unsubscribe what you don’t need
  • Filter what you only need if you search for it (i do this eg for follower updates etc)
  • Filter everything that can be automatically processed (eg all my invoices get a label, all my commercial invoices get a label and are forwarded to my assisstent who will then use it for bookkeeping)

By now i have over 100 filters and i only see new emails if i really need to see them.

Keyboard navigation

  • Enable shortcuts in settings
  • Learn them
  • Most important y for archive, r for reply, a for reply all, s for star

Auto advance

  • Choose auto-advance in Settings so you can cycle through your new emails in the morning really fast

Undo sending

  • Enable Undo send in Settings > Labs
  • Wonder for the rest of your life why this is not a default feature

Merge your email accounts to one

  • Screw multiple logins
  • Fetch all your email to your main gmail account
  • Be sure to use the “smtp” feature to avoid the emails being send as “on behalf of”

  • Choose to always reply from the email you got the message sent to
  • Ideal if you have private and professional emails coming now to the same inbox

Install rapportive. But i am pretty sure you already have done so. ;)

Update:

A few people mentioned that they suggest using labels instead of stars. Labels are accessible in the mobile app and also in other apps.

Personally I prefer the stars because they are quicker to access. But if you are looking for a way to have the same workflow also accessible in your mobile - labels might be the solution.

That’s it.

I hope this workflow helps you as much as it helped me and several people i showed it too - If you want please tweet this article. And also feel free to hit me up on twitter if you have any further questions or suggestions how to improve my workflow: @andreasklinger

Until then, lifehack the planet,

Andreas

Why Lean Startup sucks for startups.

If you go to Lean Startup events you will find first time founders, consultants, accelerator managers, r&d people, enterprise intrapreneurs, people of the government and a lot of people running meet-ups around the topic of Lean Startup. But you hardly meet people who are doing startups successfully or people who are in their nth startup. Why?

Also a lot of people mention more and more than Lean Startup is moving more and more to Enterprise. And that’s plain obvious to see. But why is it happening?

All of those are merely symptoms. The underlying fact for that is quite simple.

Lean Startups “sucks” for startups

Disclaimer:

I am not bashing Lean Startup in this article. I critisize it in its current iteration. Lean Startup will look different in a few years from now. And hopefully incorporate my concerns.

The problems i mention could be blamed on those who practice, or those who teach. But honestly it’s a problem with in-difference and loosing touch to startup reality.

It comes down to one thing: treating enterprise and startups the same and a cargo-cult like process by 3rd tier experts (like me) who increase the negative effects of this anti-pattern.

Many experts (incl. book authors) are giving processes and tools to enterprises and startups without truly understanding their different context and needs. And there is a reason why Lean Startup works best in enterprise and education (right now). Because that’s were those tools work best.

Let me explan…

Upside Validation vs Downside Protection

Startup life is about protecting your head and not your ass. Because your are running head-forward in the dark.

The goal of a startup is not to validate as much as possible to be sure that you are on the right track. The goal is it to validate as little as needed.

Startups are not about validating you do the right thing. Startups are about validating you are not doing the wrong thing.

It sounds very similar but it is fundamentally different.

Validating every step to get more certainty makes sense for some - eg. people who work in enterprises. But not for normal startups.

And unfortunately most people and most techniques in Lean Startup tend to ignore this different context.

Too many consultants approach this problem indifferent…

And honestly if you could measure loss of lifetime because of mediocre advice, many Lean Startup consultants would be serial killers.

Validate as little as possible

The next time someone asks you “did you validate this?” - answer “how much is it worth to validate this?”

The problem is quite simple:

  1. The time and effort it costs to validate something is usually higher then the pay-off
  2. It is usually easier to validate that you are on the wrong track. Than that you are on the right one.
  3. In many cases it pays off to move on if you are certain “enough”. Because most likely more (noisy) information won’t lead to more certainty.

Example

Let’s say you have the doors A B C or D to go through.

In a perfect world we could now evaluate all four doors (eg through interviews or experiments) and then try to make a educated choice. We could easily argument afterwards why we picked a decision. We did the right thing.

In theory this sounds like the right thing to do. Gather more data than you can cheaply acquire. Validate your decisions based on data.

Or we could pick the one we believe the strongest in (given the information we could timely acquire) and try to figure if it’s the wrong one.

This sounds like a suboptimal option, because maybe one of the others would have been the better option.

What i notice is that many people try to pick the first option, but end up with the same level of decision quality as in the second option, plus a bunch of fluff non actionable data, gathered by suboptimal methods that pseudo-justifies their decision.

  • In theory startups are about finding the right door.

  • In reality your own subjective bias combined with very noisy information will make it impossible to get to the information quality you hope for.

  • In reality you have huge risk associated with your cost of delay.
  • In reality you are happy if the door you will pick is not a death trap and you want to verify that.
  • In reality there is no-one questioning you apart of you - so all your steps should just happen to make sure you can convince yourself and that YOU do not lie to yourself.

If you are unsure what i mean with cost of delay or in general want to read about product management i recommend these slides by Don Reinertsen - here is a good summary

There is no point in trying to validate just to get the affirmation to move on. If you are already convinced most likely you will bias the output and waste time. No-one will ask you if you fail anyway. You want to make sure you are not doing the wrong thing and move on as fast as possible. And wait for the real risks to test.

Lean Startup calls it picking the riskiest assumption first. But leave it there. For startups “pick only the riskiest assumptions” might be a better formulation. It comes as said down to a mindset:

Good teams don’t use the tools of Lean Startup / Custdev as a navigation systems. They use it as a headlight to make sure they don’t kill anybody or get of the road.

You can easily argue that the behaviour I mention above has nothing to do with Lean Startup but the way how people apply it. Which is true.

Which leads me to the second big problem Lean Startup has…

Processes vs Principles

To explain this to people less familiar with Lean Startup. There are two approaches to Lean Startup:

  • Understanding it as a strategy, so to say as a process to follow.
  • Understanding it as a principle, so to say as a toolbag to use.

Similar to church members it depends to whom you speak - this definition of Lean Startup will range from that loose principles to a concrete process. And similar to lessons in the bible people tend to pick the side and lessons based on their church they belong to and the argument they are trying to win.

Btw from my talks to Eric Ries i would put him definitely into the second group. People who look for the underlying principles and evolve processes over time.

But the problem is that there is a huge cargo cult around Lean. A cargo cult of consultants and Lean Lurkers. A cargo cult that focuses on processes.

Lean Startup tends to attract people who like to be told what they should do next. And people who like to teach people that process for money. – Bjoern Lasse Herrmann, Startup Genome

People follow motions instead of understanding why they actually use certain tools.

When you don’t apply critical thought and strategy to your startup and conversations, you’re just going through the motions: replacing the hard task of strategy with the lazy solution of following someone else’s process. - Rob Fitzpatrick

Many teams become what i called above Lean Lurkers.

Teams that use complex terms and slow processes they borrow from Lean Startup to hide, and even excuse, the fact that they have no traction. No traction is no traction. No matter what you did to (not) get it.

Following Lean Startup step by step sucks for startups, but that’s ok

There is a space where you need to explain why you picked a decision. A place where you need to justify and cover your ass. A place where you want to show your updated business model canvas. A place where more data, proof and validation that fundaments your previous decision is good. The enterprise corporation.

And i mean this without any disrespect towards large corporations.

Lean Startup is one of the best things that happened to enterprises.

Because Lean Startup can help enterprises remove mid-level management decision. The moment someone outside of a project needs to touch or decide upon a project either quality or speed goes down. Lean Startup provides a framework where (in a utopian) company, opinions and politics can be reduced through data aggregation and validation to the point that they are no longer relevant.

And there is a space where you need to go through motions for no other reason than to go through the motion and be questioned at each step and learn the skills. That space is called education.

Lean Startup is a perfect vehicle for accelerators and universities to teach tools of entrepreneurship. It’s perfect to increase the contact surface with different approaches and provides an optimal framework for high paced learning experiences.

And coincidentally these are the spaces where Lean Startup currently fits perfectly.

Just to clarify:

Both problems i mentioned above - unnecessary upside validation and blindly following processes of “opinion leaders” - have per se nothing to do with Lean Startup. Lean Startup even promotes the idea of quick (potentially wrong) decisions and going for the riskiest bits first in its core.

But an undifferentiated approach to Lean Startup by treating enterprise and startup context the same leads to startup teams looking for validations only enterprises and education spaces can effort.

So if you wonder why Lean Startup moves to enterprise?

That’s the reason. In it’s current form it fits best to enterprise. It’s current leaders focus on enterprise.

The reason simple: Many people doing those workshops lost themselves in theory and forgot about the practice.

Enterprise consultants will only develop tools for enterprise people. And if you look around in the Lean Startup scene, all the current opinion leaders make their money with enterprise consulting.

Lean Startup lost a part of its core.

The problem Lean Startup has currently is (imho) that it lost the attachment to a good part of it’s core.

It used to be about the experience and best practice of startup founders. It used to be about taking that startup founder learnings and abstracting them and sharing them to more people. Founders are the ones developing new entrepreneurial tools for startup founders, not enterprise consultants. And that’s why many founders replaced their Lean Startup books with Hackernews articles.

That leaves learning opportunity for new learnings on the table. That being said - try to join the next Leancamp in your neighbourhood. We try to escape consulting land and focus on things learned by founders. Most of them come btw from other fields than lean.

What will happen with Lean Startup

I personally see two things possible to happen. Lean Startup might cut the corner and regain credibility within the startup founder scene. Which is still possible because i personally strongly believe in Eric Ries’ point of view of an evolving tool for entrepreneurship and his marketing skills to get the right people involved again.

Or not…

But even if not…

One thing I realised this year at the Lean Startup conference after speaking with Eric Ries and Ash Mauraya… It would be ok if Lean Startup doesn’t make it back to the startup scene.

Because Lean Startup itself moved on. It hit the mainstream. It became a synonym for high-paced, iterative, high-potential entrepreneurship. It became a framework for other industries to understand “how the kids in software tech do it”. It helps governments. It helps people pushing entrepreneurship.

In any case it did important big steps for entrepreneurship. And no matter if the next steps will have the same branding or another new shiny one. Lean Startup moved entrepreneurship forward.

What are your thoughts about this? Am i right? Am i wrong? Hit me up on twitter

Until then, push learning forward,

– Andreas

AngelList is the NASDAQ of our generation.

It’s fair to say that Angellist is the most exciting (web/mobile) tech startup in 2013.

Even before they launched syndicates, earlier this year, they were already heavily integrated into our startup ecosystem. They were (and are) mapping all relationships in an ecosystem that heavily relies on leveraging its social networks. Relationships like investor introductions, teams, jobs and even applications to accelerators. Needless to say this is already very big.

But since the launch of investments and syndicates there is no more stopping them. Right now it is hard for me to even imagine the potential ceiling that Angellist could face in the next years.

We are living in exciting times.

Investments changed in the last years. From long and slow processes to pitch event focused accelerators to single page applications like Kima15 of Kima Venture.

In the next years early stage investments will be closer to APIs requests or figuratively speaking going to an ATM than it is to our current investment processes, which very often still look like later stage VC/risk investments.

The future of early stage investments:

Application through Angellist, automatic due diligence through APIs, background check through social connections, in face meeting via hangout - boom money, here we go.

And Angellist is in the heart of all of this.

Angellist is the NASDAQ of our generation.

“The private market is at the stage the public market has been in the 80/90s” – Paul Singh.

Right now we are just seeing the beginning. Syndicates make it effective for investors to join the best rounds, and more importantly **syndicates make it easy for the upcoming waves of me-too angels to join the game. **

There are a few logical implications what might happen next. Here are my three predications.

1) Secondary markets

Sooner or later, given the legal complications – AL might transform into a real stock exchange. Why just buy your equity of startups. Why not sell it as well?

We have currently two interesting problems in startup investments:

Companies are pushed to exits (IPO, acquisition) to provide liquidity for the stock holders. And those exits often cripple the product ambition of a startup.

Not all of the startups of our generation will be optimal candidates for IPOs and exits. Leading to the need of alternate returns (evergreens eg). For some investors this fit. Some might want to leave a bit earlier.

Obviously (speaking as a laymen) this needs a few changes how we address stock of private companies or other special legal regulations.

But if there is a company that has the best position to make this happen it’s Angellist. Angellist is the NASDAQ of our generation.

When will this come:

Given the legal complications and the fact that AL is still just a very small team i wouldn’t be surprised if this will need a bit more of time or might come through a partner in the beginning. But me for me personally this is where i see AL’s main role in a few years.

2) Onboarding of new me-too investors

There is a huge wave of late-to-the-game/me-too investors/wanna-be-angels coming to the market right now. These people need education and access to knowledge/experience, because – frankly speaking – there will be certain changes in investor types.

The “hollywoodization of startup investments” (coined by Paul Singh) creates an environment where the public persona or the social following of the investment leaders will be a more important factor than their investment experience. To normalize this, we need to education and onboarding of me-too angels. Accelerators for angels, Lean Startup Books replaced by Lean Investment books.

Currently I imagine a front-page explaining how startup investments work in reality and which syndicates or investors they should back for what reasons.

When will this come:

I don’t believe AL will or even should build this. This would be sub optimal. They should offer affiliate/provisions to people referring investors and spawn an ecosystem of tools of this kind.

If you are working on a startup in this space - let me know - I am happy to add you here.

3) Spawning an ecosystem of market analysis software

If Angellist is the NASDAQ of our generation. Who is the Bloomberg? A lot of companies try to answer this question.

Most of them aggregate public data and try to generate information/indications out of it.

There a lot of companies in this space and also a lot of VCs build their own in-house tools.

But most noteable here are Mattermark and Indicate (Indicate was previously known as dashboard.io).

One might argument that Compass.co (by the guys of Startup Genome Project) belongs into this list. I personally would disagree with that assumption (Disclaimer: I am working with the team).The focus of Compass is to provide benchmarks and insights to the startup teams themselves and to provide aggregated (anonymous) information to the ecosystem. Which itself might be an even bigger opportunity (but this is another blogpost).

Mattermark, Indicate and co pluck into Public APIs like:

  • Traffic rankings (thus estimated traffic) from Alexa, Compete
  • Social activity from Facebook, Twitter, etc
  • Appstore rankings (thus estimated downloads)
  • Investor interest via funding informations from Crunchbase or Angellist
  • Press buzz based on press releases and media mentions
  • and other similar sources

But let’s be honest… The data they currently access is very limited. And even more important - what kind of information can you really infer out this data?

“Yay, they gained 20 followers. Let’s invest” – Said no good investor ever.

But it’s not about exact information. It’s about getting as many signals as you can. In a path of darkness even a small light in your hand is better than nothing.

And truth be told, while most of us people who work with analytics worry about accuracy or precision. In the case of monitoring private companies we are still in the situation of “any data is better than none”.

If this doesn’t convince you - here are a few reasons why i believe there is a big space for opportunities:

Reasons why these tools are useful: Analogy to public markets:

The images above is a service created by UBS - they monitor (eg.) Walmart’s parking lots and by that estimate Walmart’s customer traffic (and thus revenue).

This is not exact information. But hypothetically speaking if you would be interested in investing in a retailer - it would be good to know rough ranges of visits they have. Paul Singh has an excellent presentation on this you need to read

Reasons why these tools are useful: Social Signals:

Also there is more information in public data than one would expect. Eg the social signals in the interaction with startups is a good proxy for buzz. As an angel investor would you be interested if Jeff Clavier all of a sudden started tweeting about a startup that fits your target list? Well i would be very interested. Plus there is opportunity in comparing the patterns of buzz of early stage companies with historic data of successful ones.

Reasons why these tools are useful: Alerts:

For me personally the imho most interesting service is automatic alerts about new startups. “A new wearable tech company appeared in CEE. Their angellist account is two hours old. Their CEO used to run a bigger division at Nike and their Lead engineer has a strong arduino open source following on Github. One of their early followers on twitter is Tim Ferris.” If you are into wearable tech you might want to take a look.

If you are interested in this be sure to subscribe to Nick O'Neill’s awesome Startup Stats newsletter. He features the best kickstarter/indiegogo projects.

And there is a lot of more potential in this space.

  • Stronger focus on social signalling
  • Proprietary data sources
  • Monitoring crowd financing pages like Kickstarter and IndieGogo

Should you completely base your investment decisions on this kind of tools? Oh god no.

But it’s a good way to compete with VCs who have an army of radar boys employed.

When will this happen:

It’s already happening. Mattermark is currently leading this upcoming market. Indicate is catching up fast.

The main difference is that Indicate offers their insights/data for free and only monetizes on add-on features. This is a leap-jump, given the fact that any company that monetizes on access of information sooner or later gets disrupted by the Internet. On the other hand Danielle is top of her game and thinks far ahead.

The big obvious scary elephant that no-one talks about - is of course the fact that sooner or later Angellist might extend their Traction feature.

Asked at the Startup Stats Summit this fall Naval said clearly that he sees all tools as partners in this ecosystem. Well… We will see.

4) And many more predictions for Angellist…

I could name many more predictions for Angellist - like regional offices worldwide for Angellist, API Integrations for due diligence and verification, various of additional ecosystem players around etc etc - but I think you get my point. Angellist as a platform is the epicentre of an exciting market.

We are just at the beginning of this journey: Public fundraising, transparent startup markets, market analytics.

“Everyone in AngelList is on a 6-year vesting schedule” – Naval Ravikant

We are in phase one of the most important platforms of our generation of startups.

About my predictions

As with all predictions please take them with a grain of salt.

Example: After the launch of FB platform I predicted with 100% confidence that FB would introduce a currency and maybe mobile payments through their facebook mobile clients. And that skype will die. Several years later FB still sell ads and just to annoy me, they even partnered up.

Personal lesson learned: my prediction tend to be a bit too far fetched.

So don’t wait for my “Early stage investment like an ATM” prediction to happen any time soon. ;)

That being said i would love to know your predictions. And I am sure you got good ones. Where do you see the meta-market of startup investments going to? Where do you see Angellists biggest opportunities? What could kill them (apart of the government)?

Would love to hear your thoughts - hit me up on twitter: @andreasklinger

Until then, continue being awesome and thanks for reading

Andreas

ps: This is written for a friend.